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document understanding

Document understanding involves document classification, layout analysis, information extraction, and DocQA.

Papers

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Showing 151–175 of 309 papers

TitleStatusHype
DrVideo: Document Retrieval Based Long Video Understanding—0
DUBLIN -- Document Understanding By Language-Image Network—0
Efficient End-to-End Visual Document Understanding with Rationale Distillation—0
Efficient layout-aware pretraining for multimodal form understanding—0
Enhancing Question Answering on Charts Through Effective Pre-training Tasks—0
Enhancing Visual Document Understanding with Contrastive Learning in Large Visual-Language Models—0
Enumeration of Extractive Oracle Summaries—0
ERNIE-mmLayout: Multi-grained MultiModal Transformer for Document Understanding—0
Extract with Order for Coherent Multi-Document Summarization—0
Fast-StrucTexT: An Efficient Hourglass Transformer with Modality-guided Dynamic Token Merge for Document Understanding—0
Finding Pragmatic Differences Between Disciplines—0
FormNet: Structural Encoding beyond Sequential Modeling in Form Document Information Extraction—0
Leveraging Distillation Techniques for Document Understanding: A Case Study with FLAN-T5—0
Leveraging Domain Agnostic and Specific Knowledge for Acronym Disambiguation—0
Leveraging Long-Context Large Language Models for Multi-Document Understanding and Summarization in Enterprise Applications—0
LongFin: A Multimodal Document Understanding Model for Long Financial Domain Documents—0
LoPE: Learnable Sinusoidal Positional Encoding for Improving Document Transformer Model—0
LoRA-Contextualizing Adaptation of Large Multimodal Models for Long Document Understanding—0
M3DocRAG: Multi-modal Retrieval is What You Need for Multi-page Multi-document Understanding—0
MataDoc: Margin and Text Aware Document Dewarping for Arbitrary Boundary—0
MATATA: Weakly Supervised End-to-End MAthematical Tool-Augmented Reasoning for Tabular Applications—0
MATrIX -- Modality-Aware Transformer for Information eXtraction—0
Memory-Augmented Agent Training for Business Document Understanding—0
Merge and Recognize: A Geometry and 2D Context Aware Graph Model for Named Entity Recognition from Visual Documents—0
M-Longdoc: A Benchmark For Multimodal Super-Long Document Understanding And A Retrieval-Aware Tuning Framework—0
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